 Thank you so much for joining us today for this webinar, which is entitled Factors Associated with Developing High Nutrition Risk, Data from the CLSA. We'd like to start with a land acknowledgement. The CLSA National Coordinating Center and McMaster University are located on the traditional territories of the Mississauga and Haudenosaunee Nations and within the lands protected by the Dishwith One Spoon Wampum Agreement. The University of Waterloo, which is not too far away from McMaster, where today's presenter is based, is situated on the Haldeman Tract, which is land that was granted to the six nations that include six miles on each side of the Grand River. Much of the University of Waterloo's work takes place on the traditional territory of the neutral Anishinaabe and Haudenosaunee peoples. As attendees of the webinar today, I encourage you to continue your learning following the webinar and to acknowledge the original inhabitants of the lands where we all have the privilege to research, live, and work wherever that may be for you. Before we begin to, I'd also like to go over some housekeeping points that are also on the slides in front of you. Everyone but the presenters will be muted throughout the webinar. If you need to change or test your audio during the webinar, you can just click Audio Settings, which is on the bottom of the Zoom window. At the end of today's session, there will be a question and answer period. If you have a question for the presenter during the webinar, you can post it in the Q&A box that's located in the bottom toolbar. The questions will be addressed at the very end of the webinar. And just note that questions will be visible to all attendees. And just to note that if you have questions about the webinar, put them in the Q&A. But if you have technical issues, please put them in the chat box. And a feedback survey will be launched at the end of the webinar. And we invite you to complete it after exiting the Zoom session today. This brief survey provides us with important feedback that we can use to plan future webinars like this one. Now onto today's webinar. Factors associated with developing high nutrition risk data from the CLSA. And our webinar presenter is Dr. Christine Mills. Dr. Mills is a registered dietitian and she completed her PhD in Aging in Health at Queen's University in June 2023. She is currently a provost interdisciplinary postdoctoral scholar at the University of Waterloo in the nutrition and aging lab, which is led by Dr. Heather Keller. Dr. Mills research examines nutrition risk in older adults and the nutrition education needs of older adults, as well as interprofessional healthcare providers. Her dissertation research explored nutrition risk in community dwelling Canadian adults at midlife and beyond using CLSA data. Her other research interests include naturally occurring retirement communities, interprofessional primary care, weight bias, food insecurity and unpaid care grooming. So with that, I will pass it on to Christine and the webinar today. Thank you so much for that introduction. As indicated, I'm Dr. Christine Mills. I am currently at the University of Waterloo, but the work I'm presenting today was done when I was a PhD candidate at Queen's University. So this is the paper I will be discussing. It was published in the Canadian Journal on Aging and you can access it through the QR code here. So what is nutrition risk? Well, there's really no agreed upon definition. However, it can be considered the risk of poor dietary intake and nutritional status. It can lead to malnutrition if it's not addressed. I like this definition by Dr. Heather Keller that indicates that nutrition risk represents the determinants and risk factors that place an individual at risk for poor food intake. And if not interrupted can lead to malnutrition. And this diagram here is also from Dr. Keller and it shows the relationship between determinants of and factors for food intake. And the nutrition risk, which occurs when someone's food and dietary intake does not meet recommendations for their age and gender. And you can have weight changes at this stage such as unintentional weight loss. And then again, if nutrition risk is not addressed it can lead to malnutrition. And that's when an individual's dietary intake does not meet their requirements. So you see a loss of weight, a loss of tissue, a loss of function, frailty and this can lead to adverse health effects. So what are some of the risk factors for developing nutrition risk? Well, things like food insecurity where an individual does not have sufficient income to support the purchase of healthy adequate foods. Things like dysphagia, which are swallowing difficulties that can occur in certain conditions such as stroke or with age. Poor dentition, poor oral health or other problems with chewing. And then as we age there can be physiological, psychological and social changes in our lives. And all of these can lead to low appetite and low food intake. So why do we care about nutrition risk? Like why did I do this research? Why should we care? Well, there are negative consequences to nutrition risk. So in addition to nutrition risk potentially leading to malnutrition and causing all the negative health effects associated with malnutrition. Nutrition risk itself has been associated with frailty and frailty is a medical condition of reduced function and health in older individuals. Nutrition risk is also associated with reduced quality of life with hospitalization, with early institutionalization and even with death. So this is why we should care about nutrition risk. So from previous research we know that there are many different social factors that are associated with nutrition risk in community dwelling older adults. So for example, eating alone is associated with high nutrition risk whereas eating with others can improve food intake particularly in older adults. Studies have found that having high levels of social support can reduce nutrition risk likely because individuals who need help with food related activities such as grocery shopping or meal preparation if they have good social support they will have assistance with those food related activities whereas low levels of social support have been associated with increased nutrition risk in previous studies. Infrequent social participation. So infrequent participation in community activities with others has also been associated with high nutrition risk. And as well a study conducted during the COVID-19 pandemic restrictions. So early on in the pandemic found that loneliness was associated with high nutrition risk. Now, when we look at longitudinal studies that have been done in Canada on nutrition risk there really aren't that many. So one study was a one year longitudinal study conducted in Quebec that looked at changes in nutrition risk over the course of that year. And the only item that they found was associated with increased nutrition risk one year later was poor self-rated health at baseline. Another study conducted in Ontario by Dr. Keller was an 18 month longitudinal study. She examined meal programs that included a social component so something like congregate dining or meals on wheels. And she found that meal programs improved nutrition risk scores. And also that having depression at baseline was associated with increased nutrition risk 18 months later. And finally a study conducted by Lange and colleagues that took place over the course of four years. So a little bit longer here looked at nutrition risk in men only. And this group found that there were five different trajectories of nutrition risk in this group of men. So how their nutrition risk changed over time. There were five different ways that it changed over time. And these different trajectories differed on mental health, physical aging, self-perceived successful aging and living alone. So based on this previous research, the research that I conducted, we wanted to determine which social network factors were associated with the development of high nutrition risk at follow up in individuals who were not at high risk at baseline using a nationally representative sample of community dwelling Canadians aged 45 and older from the Canadian longitudinal study on aging. And we wanted to do this using a theoretical framework. So this is the framework that we use. So we use the Berkman and colleagues social network theory as our theoretical framework. So this theory posits that social structural conditions which are the macro level condition, the extent, shape and nature of social networks which are the MISO level. And these in turn provide opportunities for psychosocial mechanisms, which are the micro level. And these then impact health outcomes such as nutrition risk. So my research focused on the MISO and the micro levels as these were hypothesized to be direct upstream determinants of nutrition risk. So if we think of this in terms of nutrition risk we can think of maybe social structural conditions. At the macro level, if there are socioeconomic factors. So say an older adult has an adult child who often comes to visit them and help them with grocery shopping and food preparation. We'll assume that socioeconomic conditions worsen and this adult child needs to now work an extra job. So has less opportunity to visit their older adult parent. Well then that's gonna affect the older adult social network because they won't be seeing their adult child as often. This will then impact that older adult psychosocial mechanisms because they won't have as much of that social support and access to resources and material goods as they previously did. And then if they don't have that social support for the help with the grocery shopping or their meal preparation well then they might develop high nutrition risk. So this is a CLSA webinar. So the data source we used in the research is the Canadian Longitudinal Study on Aging or CLSA. As many of you know, the CLSA is a large Canadian longitudinal study of more than 50,000 individuals who were between the ages of 45 and 85 when recruited at baseline between 2010 and 2015. And initial data were gathered at that time. The first wave of follow-up data were gathered three years later and I'll just be referring to that often as follow-up but it is the first follow-up. And again, as many of you know, there are two cohorts of participants tracking and comprehensive. So at baseline, there were 21,241 tracking participants followed by telephone interview only and there were 30,097 comprehensive participants who are interviewed in person, undergo physical assessments and provide urine and blood samples. And for this reason, they need to live fairly close to one of the CLSA centers. So in the tracking cohort, the proportion of individuals from each province is representative of that province's population. And for that reason, we decided to use data from the tracking cohort for this study. So because we were using a theoretical framework, we were basically able to map constructs from social network theory onto CLSA measures. So by Berkman and colleagues at the MISO level, we have social network structure. So social network size and range and the CLSA measures we used were the number of friends, siblings, relatives, neighbors and children and the number of people known through work or school, through community activities or through other activities. Also within social network theory, we have the construct of characteristics of network ties. So frequency of face-to-face contact. And for that, we use the CLSA measure of frequency of contact with friends, siblings, relatives, children. At the micro level, we were able to map psychosocial mechanisms again onto CLSA measures. So social support, this was measured in the CLSA using the Medical Outcomes Study or MOS, social support survey. Again, social engagement, social network theory construct, we used the CLSA social participation measures. And then for access to resources and material goods, we considered household income as well as self-rated social standing. Now for social network size, as I mentioned, individuals in the CLSA were asked the number of individuals in each of these groups. So these are the groups I already described. Participants were also asked the frequency or no, sorry, when they last got together with members of these groups, so children, siblings, close friends, relatives and neighbors. Now then for social participation, CLSA participants were asked how frequently they participated in several different types of social activities. So family or friend activities, religious activities, sports or physical activity with others, educational or cultural activities, clubs or fraternal organizations, association activities, volunteer or charity work, as well as other recreational activities. So we summed these to create a single social participation measure. And as that measure increased, social participation also increased. So in terms of social support, as I mentioned, they used the medical outcomes study social support survey. And this measures several types of social support, including affection, emotional and instrumental support, tangible support and positive social interactions. And the MOS has excellent internal consistency and excellent test retest reliability. For self-rated social standing, CLSA participants were asked to think of a ladder with 10 steps as representing where people stand in their communities. And at the top of the ladder are the people who have the highest standing and at the bottom are the people who have lowest standing. And then they were asked, where would they place themselves on this ladder? And then for household incomes, participants were simply asked to provide their household income from all sources. And these were the categories that we used in our study. Now, we also had some potential covariates in our research. And these included demographic factors such as age, sex assigned at birth, marital status, educational attainment and living situation. We also had some health variables as potential covariates. And these include depression, which was measured with the Center for Epidemiologic Studies Depression Measure. Disability, which was measured with the older Americans resources and services multi-dimensional assessment questionnaire. And then self-rated general health, mental health, oral health and healthy aging. And these were all measured by asking participants whether they would rate these as excellent, very good, good, fair or poor. So our health outcome of interest is nutrition risk. And I mentioned earlier why we care about nutrition risk. So in the CLSA, nutrition risk was measured using the abbreviated version of seniors in the community risk evaluation for eating and nutrition two, which has been rebranded as screen eight. So eight questions, hence screen eight, ask about typical daily eating habits, including questions on weight change, meal skipping, appetite, swallowing, servings of fruits and vegetables, fluid intake, eating with others and meal preparation. So scores can range from zero to 48 and higher scores indicate less risk. And a screen eight score less than 38 indicates that an individual is at high nutrition risk. So screen eight is a valid and reliable tool for screening for nutrition risk. And it has good specificity and sensitivity compared to registers, dieticians, assessment of nutrition risk. And so because I wanted to examine the factors associated with the development of high nutrition risk, we used data from individuals who are not at high nutrition risk at baseline. And this sample consisted of 11,032 individuals from the tracking cohort. We used binary multivariable logistic regression to examine the predictors of the development of high nutrition risk because our outcome of interest had two levels, either a person developed high nutrition risk at followup or the remained at low nutrition risk at followup. So our main variables of interest were the social network variables. But as I discussed, we also had some potential covariates in the demographic and health variables. And so we basically ran three binary logistic models. So the first model simply had the social network variables as predictors with the development of high nutrition risk at followup as the outcome. The second model added demographic variables. And then the third model added health variables to the demographic and social network variables. So when we look at the results, so first of all, the sample consisted of 11,051 individuals in total who provided data at followup. Of those, 11,032 individuals were not at high nutrition risk at baseline. And so that was our sample, as I mentioned. The mean age of participants was about 59 and a half years. About 52% were female, assigned female at birth. About 77% were married or partnered. Now at baseline, 36.5% of that larger sample select 17,000 individuals were at high nutrition risk. At followup, again in the total sample, 42.2% were at high nutrition risk. And among those who were not at high nutrition risk at baseline, about 27 and a half percent or 3,023 individuals developed high nutrition risk at followup. So as you can see, nutrition risk is highly prevalent in community dwelling Canadian adults. So when we looked at the social network variables, none of the variables at the social network or meso level were associated with the development of high nutrition risk. But in a way that makes sense, because in the theory, the social network variables are hypothesized to impact the psychosocial mechanisms. And it's the psychosocial mechanisms that affect health outcomes. So we found exactly that. We found that the psychosocial mechanisms were significantly statistically associated with the development of high nutrition risk at followup. So in our model with just the social network variables, we found that social participation, self-rated social standing, social support and household income were all associated with the development of high nutrition risk at followup. And basically the higher these were at baseline, the lower the odds of developing high nutrition risk at followup. When we added demographic variables to the models, household income was no longer a statistically significant predictor, but the others remained so. And when we had added the health variables in basically the same results. So social participation, self-rated social standing and social support were all associated with the development of high nutrition risk at followup. So if you're actually interested in the odds ratios, here they are. So in the, that included the social network, the demographic and the health variables, these were the results. So for every one point increase in social participation, so as people participated in more community activities, the odds of developing high nutrition risk at followup decreased by 2%. Similarly, for every one point increase in self-rated social standing, so higher social standing, the odds of developing high nutrition risk decreased by 4%. And then for every one point increase in social support, so again, more social support, the odds of developing high nutrition risk at followup decreased by 1%. Now, then when we look at which health variables were associated with the development of high nutrition risk, we found that those who screened positive for depression at baseline had 1.3 times the odds of developing high nutrition risk at followup compared to those who were negative for depression at baseline. Those with a self-rated healthy aging of good or fair or poor compared to those with a self-rated healthy aging of very good or excellent had 1.49 and 1.69 times the odds respectively of developing high nutrition risk. So basically as self-rated healthy aging worsened, the odds of developing high nutrition risk increased. And then finally, those who had a self-rated oral health of good compared to very good or excellent had 1.27 higher odds of developing high nutrition risk at followup. So what can we conclude this research? Well, basically there is a very high proportion of Canadian nutrition risk. So using the CLSA tracking cohort, we found that 36.5% of participants were at high nutrition risk at baseline and 42.2% were at high nutrition risk at followup. So the baseline number is similar to previously studies that have been done in Canada. So Morrison and colleagues looked at high nutrition risk in Canadians 55 and older and they found about 32.5% of individuals were at high nutrition risk. Reimage Maureen and Gariguet looked at high nutrition risk in community dwelling Canadians age 65 and older and they found about 34.2% of community dwelling older adults were at high nutrition risk. In our study, we also found that 27.4% of participants developed high nutrition risk between baseline and followup. This is a little higher than another CLSA study that used data from the comprehensive cohort where they found that 17.3% of individuals developed high nutrition risk between baseline and followup. Now, it should be noted that the comprehensive cohort because they have to live fairly close to one of the CLSA research centers, this cohort tends to be better educated, have higher incomes and be more urban than the tracking cohort. And so this could explain why the tracking cohort had a much higher percentage of individuals developing high nutrition risk because they may not have those factors. So they might not be as highly educated. They might not have as high incomes and they might not be as urban. So like all studies are strength, one strength is the use of the CLSA data set. So as I mentioned earlier, the tracking cohort is representative of Canadian provincial populations. The measures used in the CLSA are all valid and reliable measures. It's a large sample. And at the time that we made our data application, there were two waves of data. So we were able to look at nutrition risk longitudinally and look at what was associated with the development of high nutrition risk. And another strength was the use of a theoretical framework. So we weren't just choosing our variables for no reason or because we thought they were interesting, they were actually based on a theory. So of course, all studies also have their limitations. So despite the tracking cohort being representative of provincial populations, there are some populations that are not included in the CLSA. And these include full-time members of the Canadian Armed Forces and as a former regular force military spouse and now as a reserve force military spouse. This is something that bothers me because I'm really interested in nutrition risk in military members. The CLSA tracking cohort also does not include individuals who live in the territories and in some remote areas. It does not include individuals who live on First Nation reserves and settlements. And the tracking cohort largely identified as white when asked about their ethnicity. So 97.4% indicated their ethnicity was white. And CLSA participants had to speak English or French to be able to answer the questions. Now, when it comes to the variables we used in our study, so for the frequency of contact with network members variables, the CLSA only captured face-to-face contact with network members. And we know that people stay in touch and have social connections through many other means. And we certainly saw this throughout the lockdown portion of the pandemic. So people made use of video chats like Zoom, like what we're on today. People text each other, people email each other, people telephone each other. Some people telephone their older parents daily or text them daily. So there are many other ways that we can have social connections with others beyond face-to-face social interaction. And so that's a limitation of our study is that we didn't look at these other measures of social connectivity. As well, it should be noted that screen H, although it is a valid and reliable tool for determining nutrition risk in community dwelling older adults, its validity and reliability have only been established for individuals 50 years of age and older. Now, I purposely chose food jewels from 45 to 50 years of age in my study because I'm interested in seeing how their nutrition risk changes as they age, as they move from middle adulthood into older adulthood. So future research plans of mine include using future CLSA waves to examine that change. So that's why they were included here so I can examine that change over time. So what can we conclude from this research? So we found that social factors were associated with the development of high nutrition risk. And so low social support, low social participation, solo participation in community activities, low self-rated social standing and low income were all associated with the development of high nutrition risk. So if we want to reduce the prevalence of nutrition risk and prevent some of the negative outcomes associated with high nutrition risk, we need to develop programs and policies that are designed to provide individuals with social support, particularly when they need that help with food related activities. We need programs and policies that foster social participation. And we need programs and policies that provide adequate income. Additionally, we should screen individuals with low social support, low social participation, low social standing and low income for nutrition risk so that we can intervene before the nutrition risk develops into malnutrition. And the only way we know if someone is at nutrition risk is by screening them. Similarly, we found that depression and low self-rated healthy aging were associated with the development of high nutrition risk. So once again, if we want to reduce the prevalence of nutrition risk, we need to identify and address depression. And again, with the primary care crisis in Canada, not everyone has access to a primary care provider. And so they might not be properly identified if they have depression. We need to design programs and policies that encourage healthy aging. And again, we should screen individuals with depression or with low self-rated healthy aging proactively for nutrition risk. So again, we can intervene if they are at nutrition risk. So I briefly touched upon this, but based on this research, we have ideas for future research that we can do with future waves of CLSA data. So it's wonderful that CLSA participants are followed every three years for 20 years or until participant depth. So we'll have a lot of great data that we'll be able to continue to examine nutrition risk longitudinally with the CLSA. So one thing we can do is examine nutrition risk and the development of high nutrition risk by age group. And I have done this and these papers are either currently under review or are about to be submitted to a journal. We can examine additional factors associated with high nutrition risk and the development of high nutrition risk. So we can look at additional variables that have been identified in the literature and that are also present in the CLSA data set and see how those are related to the development of high nutrition risk. With future waves of CLSA data, we can, as I said, continue to examine this longitudinally. We can describe trajectories of nutrition risk over time. And as I said, I'm particularly interested in examining how nutrition risk changes as adults at midlife move into older adulthood. So this work was done as papers have been published, which are also part of my doctoral dissertation. And so these are here and those QR codes will bring you to the papers. So in the first study, I used latent class analysis to derive the social networks that Canadian adults 45 to 85 belong to using the baseline data from the CLSA tracking cohorts. And I found that individuals belong to one of seven different social network types and the social network types ranged from diverse. So large networks, many different connections, many different types of connections, high participation in community activities, too restricted. So restricted small networks, very few connections, few types of connections and low participation in community activities. And we found that screen eight scores and high nutrition risk were associated with social network type. So individuals belonging to more diverse networks had higher screen eight scores and a lower prevalence of high nutrition risk. Whereas the individuals belonging to more restricted network types had a higher prevalence of nutrition risk and lower screen eight scores. And these relationships held even after we controlled for demographic variables. So the second study here, we examined the social factors associated with screen eight scores at baseline and then at first follow-up. And similar to the findings presented here on the development of high nutrition risk, we found that individual higher social participation, higher self-rated social standing and higher levels of social support had higher screen eight scores at both baseline and follow-up. And then among the demographic variables, we found that individuals who were single or widowed compared to those who were married or partnered had lower screen eight scores at both time points and individuals who screened negative for depression and those with higher self-rated general health, healthy aging and oral health had higher screen eight time points. So the final paper from my dissertation work that looked at changes in screen eight scores between baseline and first follow-up has recently been accepted to the Canadian Journal of Dietetic Practice and Research. So that will be available soon if you're interested in this topic. So I'd like to thank my doctoral supervisor, Dr. Catherine Donnelly. I'd like to thank my committee members, Dr. Heather Keller and Dr. Vincent DePaul. And I'm very fortunate that Dr. Heather Keller is now my postdoctoral supervisor. Of course I'd like to thank the Canadian longitudinal study on aging for providing the data and all the CLSA participants for taking part. I'd like to thank the CHR summer program in aging that I attended, which was on longitudinal studies such as the CLSA. And I was supported by an Ontario graduate scholarship, Queen Elizabeth II graduate scholarships in science and technology, the support our troops national scholarship from Canadian forces, morale and welfare services and by Queen boards and research fellowships. So March is nutrition month, which is why I'm presenting on nutrition in March. And tomorrow, March 20th is dietitians day. So if you're interested in nutrition, you can find lots of information on nutrition month online. So thank you kindly. And if you are interested in nutrition in older adults, not only in the community, but also in other settings such as long-term care, I'm currently a member of Dr. Heather Keller's nutrition and aging lab. And here's our lab website and you can find out all about our research there. So thank you and I'm happy to take any questions. Great, well, amazing job. So you're very enthusiastic, I love it. And actually those pictures on that slide are making me feel very hungry right now. Yes, it's lunch. Yeah, I know. So again, thank you very much. I'd like to open it up to questions. There's already several that have come in. Just a reminder to, if you have questions to post it in the Q and A box, which is in the very bottom of the screen. So the first question is actually more of a comment that you can comment on that came in. And it is that your definition of nutrition risk overlaps with the diagnostic criteria of major depressive disorder. If your research did not include patients with major depressive disorder or did not study the interaction between nutrition risk and major depressive disorder, I would suspect the confounding of mental illness was not accounted for in your research. So anything to comment on related to that or did you look at that? Yes, so as you can see in our full model, so our full model included the social network variables, the demographic variables and the health variables. So depression screening positive or negative for depression using the CESD10, the depression screening tool valid and reliable in older adults. So that was one of the variables we included in that full model. And as you can see here, screening positive for depression was associated with the development of high nutrition risk at follow up. And the next two questions are from the same person. The first one, did you differentiate between living alone and eating alone in your study? It seems that eating alone was not part of the screenate tool. And then the next question is, can you go to the screenate, slide again and explain how the sensitivity and specificity can be guaranteed? So maybe go back to that slide and answer both. Yes, so just because you live alone doesn't necessarily mean you eat alone. So where's my screenate? I skipped over it, didn't I? Yes. So you can live alone but still eat with others. So for instance, lots of older adults who live in the community who live alone may attend what we used to call senior centers. The word senior is considered ages. So an older adult activity center and older adult recreational center, they might go to one of those for lunch. Or if they live in a retirement home, they might get one meal a day and that might be lunch. So they're eating with others. So living alone does not necessarily mean eating alone. And the screenate tool does actually ask about eating alone or with others. So that's one of the eight questions in the screenate tool. And in the chat, they put in the older adult nutrition screening website. So that's a website from Dr. Heather Keller who is the screen tools. And there is information on how to use and score the screen tools on that website. Loads that address each of the factors that the screen tools ask about. So there's a handout on hydration because as you can see in screenate, fluid intake is one of the questions. So eating with others or eating alone questions in screen. But that doesn't necessarily mean a person who lives alone eats alone. So living alone was not part of the screenate tool but we did include it as a demographic variable in our model that included the social network and demographic variables as well as in the full model. And any comments on the sensitivity and specificity of the screenate? Yes, so there's a paper published by Dr. Heather Keller, the creator of the screen tools that goes into quite some depth on how the validity and reliability were established but basically registered dietitians like myself or other research dietitians assess the nutrition risk of older adults using a different tool that looks at things like health status, functional status, health conditions, things like body mass index. So body mass index had to be measured, height and weight needed to be measured, things like hand grip strength, four meter walking speed. So taking all of those factors into account, dietitians determined whether an individual was at low moderate or high nutrition risk. And then those determinations by the dietitian were compared to the results that the screen tools have and the beauty of the screen tools is they don't need those measures. You don't need to measure someone's height and weight. You don't need to know what someone's hand grip strength is. You don't need someone's four meter walking speed. So screen can be self-administered to administer what is required. And so when comparing the results from the screen tools to that registered dietitian assessment when the registered dietitian does this more in-depth determination of nutrition risk, the screen tools had good specificity and sensitivity when compared to those dietitian assessments. And again, you can find the paper, if you're interested, it's by Keller and colleagues and it's on the validity and reliability of screen, probably screen two as it was known at the time. So if you search for that paper, you'll find it. Or if you go to our Nutrition and Aging Lab website, you can find Dr. Keller's information there. Great. Next question, just sort of moving down the list. What have your earlier studies shown you regarding members of the Canadian Armed Forces and nutrition risk in members of the Canadian Armed Forces? That's not research I've done, it's research I want. As like I said, I'm now a reserve spouse because my spouse is now following me, but prior to this, he was regular force and I was following him. So I'm really interested in the diets of Canadian Armed Forces members and their families. So hopefully that's another future research project. Perfect, well, it's all about building the program of research, so lots of opportunity there. Yes. Okay, so the next question is about the screening tool and questions about weight. Many public health units are aiming to be weight-neutral in language and to focus on health behaviors as opposed to weight. However, weight can be an important indicator of nutritional risk and frailty and older adult question. Are there any recommendations or suggestions of how to use and promote effective screening with a more weight-neutral lab? Good question. Yes, that's a really good question. Actually, I delivered a webinar on this for the weight-inclusive dietitians of Canada group. So there is a weight-inclusive group of dietitians in Canada and they offer webinars similar to what the CLSA does and I actually presented a webinar on exactly this, like how can we still look at nutrition risk while taking the focus off of weight? And so in my previous research in naturally occurring retirement communities, so basically communities that just happen to have a large number of older people living there, they weren't purposely designed for older people, but just the way they naturally developed, there's a lot of older people living there. And so when I looked at the factors associated with nutrition risk in that group of individuals, weight loss was not consistently associated with nutrition risk. So it is important because we know if someone is losing weight unintentionally, they might be prone to developing nutrition risk. They might be prone to developing frailty. So it's something I struggle with because I always try to be weight-inclusive in my practice when I was working in primary care and I've written about weight bias in dietetics and I've written an ethical case study about weight management in older individuals. And so it's something I really struggle with, but it is an indicator to us. It does provide us with information. And maybe if we wanna be weight-neutral instead of asking it weight, we need to physically look at a person and see if there are signs of muscle wasting or muscle loss. But then again, you can't self-screen that way. You need someone to look at the person who has clinical judgment and tell if there has been that muscle loss or wasting. So it's definitely something that I feel attention about, but we do know that unintentional weight loss is a sign of various conditions. So it's important to look at. Right, so next question is, did you consider living close to an open market area or farm as an influencing factor? So I didn't have that information in the CLSA dataset that I asked for and was provided. So when you apply for CLSA data, you have to clearly indicate which variables you're gonna use. And then afterwards, if you think, oh no, I wanna include this. And if it's in the CLSA dataset, well, it's too bad you have to put in another data application, right? And that costs money. So as a student, I was able to get my data for free because I was a doctoral student, but now as a postdoctoral researcher, or if I start my own independent research program, I'll need to pay for that data access. And as a PhD candidate, I didn't have that kind of money on it. So I'm not even sure what's in the CLSA dataset regarding that, but it wasn't in the data I had access to. Yeah, I'm just to follow up, you're right. I don't believe there's a question specifically about that unless somehow you were looking at where participants lived relative to a data collection site. So there would be ways to look at geography, but not necessarily, there's no specific questions about that. But you're right, like an amendment could have been submitted and those are done in order to support research and questions. Sometimes things do change once you submit an application and we try to be as supportive of possible to make sure those amendments can get done. Okay, so a couple more and we do have a few more minutes. So any health problems included or controlled for other than depression? I thought you might have spoke about that. Yes, yes. So we can see here, we included depression, we looked at disability, which was measured with, as I said, the ORS multi-dimensional assessment questionnaire and then self-rated general health, mental health, oral health and healthy aging. Again, because these have all been previously shown to be associated with nutrition risk in previous studies. So that's why they were included. And another question, can you explain the reason the study only included face-to-face contact? So that's because again, that was the question that was asked by two CLSA participants. So CLSA participants were asked, when was the last time they got together with members of those various groups? Now there was a variable that looked at using social networking sites, so things like Facebook and Twitter and LinkedIn and Instagram and all those things. Whether people use those to stay in touch with family and friends, but unfortunately, there was a huge amount of missing data for that variable. And when I looked at it, it just like, it would have reduced my sample size so significantly. So I chose not to include it after consulting with my doctoral supervisor at the time. And it's definitely a limitation for the CLSA. We'll be asking about staying in touch with people, but for the data I had that social networking variable had a huge amount of missing data, so it wasn't really useful. Yes, there's definitely a lot of data available to researchers and if you are a researcher and you haven't gone into the CLSA's website to see the data and the different variables do so. And you may find some variables that will be quite of interest, but sometimes you do, there are missing things and or you find a variable and then there's missing data. So once you get into it, there's lots to explore and that's the idea of the CLSA data platform. I think the last question that's here is from Danelle. There is so much research like yours which shows that isolation leads to many problems. I'm always surprised that given this research, provincial governments are still advocating and funding better at home type programs. Any comments on that? Well, I think one of the issues is that people do want to age in place. So they want to age in place at home as long as possible. They want to age in place in their communities even if that means downsizing from the home they're in but still staying in their familiar communities. We know that most older adults do not want to go into long-term care and many don't even want to go into retirement residences or can't afford to go into residence because there's that middle group of people who have high enough incomes that they don't qualify for the socially supportive housing provided retirement type homes but they don't also earn enough to be able to pay for a private retirement, two or three meals a day and house cleaning and that kind of support. So given that most people want to age in place in their communities, I think that's why we're so focused on supporting people at home. We know hospitals are overcrowded. We have lots of people in alternate level of care in hospitals who could be supported at home with better support or who actually need to be in long-term care because level of support. So it's thinking of new ways of helping people remain socially connected while they're still at home and that's some of the other work I've done looking at naturally occurring retirement communities and again, my doctoral supervisor, Dr. Catherine Donnelly and one of my committee members, Dr. Vincent DePaul they're very much interested in the programs in these Norx or retirement communities and their program is called OASIS. Again, OASIS senior, you'll find the website and it's based on three pillars. So three things that can help support us to age in place and that's nutrition. So this is where I came in. I was very interested in that piece, physical activity so people can remain physically active within their capabilities. So if that's chair yoga or chair exercise, that's great. That's still being physically active. And then the final component is socialization. So having that social interaction with people have some support with others. And so we published on that and yes, people really found that this program, OASIS gave them a reason to get up in the morning. It gave them a reason to get dressed. They really enjoyed that social connectivity with other. Even when talking about nutrition, one of the quotes was it was the food and the fellowship. So it's not just having that nutrition programming but it's having that with others and having that social connection over food. Cause again, we know food is so much more than just nutrition, right? Food is family, food is culture, food is social connection, food is celebration. So yes, it's really important to try and think of other ways we can foster social connectivity while keeping people aging in place in their communities for as long as possible and as long as it's safe for them to do so. Long answer to that question. But yeah, it's another area I'm really passionate about. We probably just have time for this one last question but for those of you who are leaving, just don't forget to complete your evaluation upon exiting but we'll first we'll answer this before we finish up. I'm doing a nutrition research on CLSA and my favorite exposure is salty snacks intake. As a registered dietitian, I would like to know your thoughts about this variable. Can it be a representative of an unhealthy habit that is related to both salt intake and behavioral problem? What confounders do you think I should consider? Oh yes, well there's so many confounding issues with that. So just to use a personal anecdote, I'm a distance runner so I trained for over 14 half marathons. I've done three full marathons. I've done a couple of sprint triathlons. I just love distance running. I have no speed but I've got lots of endurance. So I found when I was running these long distances, I was getting a lot of calf cramps. I was really in a lot of pain and I was basically told it will increase your salt intake. So salty snacks, my go-to snack were salted pretzels and guess what, it helped. So depending on how physically active someone is, that's definitely a confounder because someone who is physically active might need higher salt intake and might choose salty snacks to obtain that intake. People with migraines, some people with migraines, when they get the aura, the coming on of the migraine, having something salty like potato chips and something with caffeine like a regular full Coke, they've mentioned that can help keep the migraine from proceeding if they catch it early enough. Some people need to limit their salt intake because they might have familial hypertension or just regular hypertension. And advise to limit their salt intake. So salty snacks aren't necessarily all unhealthy or eaten always for unhealthy reasons or reasons why people with salty snacks that are more health supporting. Maybe she can follow up with you a little bit more after the webinar for additional insights. But for now, I think we have reached one o'clock. So thank you again for your webinar today and your very enthusiastic answering of questions and very detailed. I'm sure everyone that attended will take something away. I'd like to remind everyone also that the next deadline for data access applications is April 10th of 2024. You can visit the CLSA website under Data Access to review the data that's available as well as additional details about the process. I'd also like to remind everyone to complete their survey upon exiting today. Finally, our next webinar will be associations between differential aging and lifestyle environment, current and future health conditions. It will be presented on April 18th by Dr. Bo Kow from the University of Alberta. And registration details are posted on our website and they're also in the chat box. You can also follow the CLSA webinar series using the hashtag on Twitter, now known as X at clsa underscore ELCB. And I think that's a wrap for today. So thanks everyone.